Traffic congestion is an ever increasing problem, particularly, in urban areas. Since the urban areas are usually populated, it has become difficult to travel without incurring delays due to traffic congestion, accidents, and other problems. It has become necessary to monitor the traffic congestion in order to provide travelers with accurate and real-time traffic information to avoid problems.
Several traffic detection systems have been developed in the past few years for detecting the traffic congestion. Such traffic detection systems include a system comprising a plurality of user devices, such as mobile phones and smart phones communicating with a central server, such as a backend server, through a network for detecting the traffic congestion at various geographical locations. The user devices capture ambient sounds, i.e., the sounds present in an environment surrounding the user devices, which is processed for traffic detection. In some of the traffic detection systems, processing is entirely carried out at the user devices, and the processed data is sent to the central server for traffic detection. While in other traffic detection systems, the processing is entirely carried out by the central server for traffic detection. Thus, the processing overhead increases on a single entity, i.e., either on the user device or the central server, thereby leading to slow response time, and delay in providing the traffic information to the users.